implemented getProject, added to notebook

Author: KtrauM

main.py

@@ -6,6 +6,7 @@
 initDatasetIncrement = "/api/deviceApi/initDatasetIncrement"
 addDatasetIncrement = "/api/deviceApi/addDatasetIncrement"
 addDatasetIncrementBatch = "/api/deviceApi/addDatasetIncrementBatch"
+getProjectEndpoint = "/api/deviceApi/getProject"
 
 #
 #  Uploads a whole dataset to a specific project
@@ -21,6 +22,16 @@ def sendDataset(url: str, key: str, dataset: dict):
     except req.exceptions.RequestException:
         raise "error" #TODO
 
+#
+# Returns the all datasets and labels belonging to a project
+# Can be used for further processing
+# @param {string} url - The url of the backend server
+# @param {string} key - The Device-Api-Key
+#
+
+def getProject(url: str, key: str):
+    res = req.post(url + getProjectEndpoint, json = {"key": key})
+    return res.json()
 
 #
 #  @param {string} url - The url of the backend server

notebook.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -35,7 +35,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -47,14 +47,14 @@
     }
    ],
    "source": [
-    "res = req.post(\"http://localhost:3000/api/deviceApi/getProject\", json = {\"key\": key})\n",
-    "dataPoints = res.json()['datasets'][0]['sensors'][0]['data']\n",
+    "project = edgeml.getProject(\"http://localhost\", key)\n",
+    "dataPoints = project['datasets'][0]['sensors'][0]['data']\n",
     "print(dataPoints)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -88,14 +88,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Feature Extraction: 100%|██████████| 30/30 [00:00<00:00, 316.30it/s]"
+      "Feature Extraction: 100%|██████████| 30/30 [00:00<00:00, 327.22it/s]"
      ]
     },
     {
@@ -160,7 +160,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -170,7 +170,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -338,7 +338,7 @@
        "max                     0.960000          0.960000          0.960000  "
       ]
      },
-     "execution_count": 7,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -355,7 +355,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -364,7 +364,7 @@
        "RandomForestClassifier()"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -377,14 +377,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "accuracy_score train : 0.5093333333333333\n"
+      "accuracy_score train : 0.5066666666666667\n"
      ]
     }
    ],